code: def results_long():
      return pandas.DataFrame(
          collections.OrderedDict(
              [
                  ("Trial-ID", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]),
                  ("Status", ["COMPLETED"] * 10),
                  ("Iteration", [1] * 10),
                  ("dropout", list(numpy.random.uniform(0, 0.5, 10))),
                  ("lr", list(10 ** numpy.random.uniform(-7, -1, 10))),
                  (
                      "activation",
                      list(
                          numpy.random.choice(
                              ["relu", "tanh", "sigmoid"], 10
                          )
                      ),
                  ),
                  (
                      "num_hidden",
                      list(numpy.random.random_integers(100, 300, 10)),
                  ),
                  ("Objective", list(numpy.random.random(10))),
              ]
          )
      )
  
imports: import sherpa
  import pandas
  import pytest
  import numpy
  import collections
  import GPyOpt
  from sherpa.algorithms.bayesian_optimization import GPyOpt
  from sherpa.algorithms import Repeat
label_desc: Use image node_id 3 for calling a global function with example usage: results_long() and returns: pandas